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A Method and System for Issue Prediction for critical IT application

IP.com Disclosure Number: IPCOM000246937D
Publication Date: 2016-Jul-18
Document File: 3 page(s) / 57K

Publishing Venue

The IP.com Prior Art Database

Abstract

With Bank business grows rapidly, Banking application become very complex in the IT environment. Therefore, IT application issue become hard to resolve. And the issue of banking field is more critical for its business importance. Bank IT maintenance team often is required to keep the system alive at 99.999% of whole service time. So IT issue prevention is a big challenge for Bank IT maintenance team. We introduce a general Analysis Framework for IT Issue prediction include analysis all the factor related to software quality from software engineer lifecycle, factor Extraction and calculate factor value from existing IT application, apply machine learning method on the calculated data and find the risk of onboarding application.

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A Method and System for Issue Prediction for critical IT application

With Bank business grows rapidly, Banking application become very complex in the IT environment. Therefore, IT application issue become hard to resolve. And the issue of banking field is more critical for its business importance. Bank IT maintenance team often is required to keep the system alive at 99.999% of

whole service time. So IT issue prevention is a big challenge for Bank IT maintenance team.

From our finding ,there are over 30 percentage issues are related to change such as new application onboard. So how to predict the failure of new application is an effective way to help maintenance team to prevent issue happen.

A General Analysis Framework for IT Issue prediction is introduced by this disclosure:
1, Analysis all the factor related to software quality from software engineer life cycle
Based software engineer concept, Extract factors from people, technology, process and product.

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2, Factor Extraction and calculation from existing IT application such as ITIL (Information Technology Infrastructure Library), HR system and meeting minutes

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records.
3, Use Name entity recognition technology to mine the factor instants from IT incidents
4, Date process to merge all related records of existing IT application to build training sample data
5, Apply machine learning method on the training sample data built at previous step to generate classifier
6, when a new application...